Sympathetic nerves and parasympathetic nerves, both of which belong to human autonomic nervous system, are closely related to the daily operation of a human body. Autonomic imbalance may induce various acute and chronic diseases, for example, heart disease, hypertension, etc., and may even lead to a sudden death, if serious. Even healthy individuals suffering from autonomic disorders may have palpitation, dyspnea (shortness of breath), gastrointestinal disorders, insomnia, etc. Hence, the protection for autonomic nervous system is not only an important issue in medicine but also a personal concern to an individual everyday. Living quality depends on how well our autonomic nervous system functions. Signs and symptoms of certain severe diseases at an early stage are attributable to autonomic disorders. Hence, early detection of autonomic disorder in an individual or a patient is likely to lessen or even prevent tragedies.
In the past, numerous instruments and methods for evaluation of autonomic functions were developed, including heart rate variation with deep breathing, valsalva response, sudomotor function, orthostatic blood pressure recordings, cold pressure test, biochemistry test, etc. However, the abovementioned methods either cause the patients much pain by requiring them to immerse in water during the test, or require expensive instruments. Hence, the above-mentioned methods are not fit to be used widely. In addition, some of these methods are difficult to use because of poor precision.
A normal adult's heart rate is about 70 beats per minute. The regular beating originates in a pacemaking system of the heart, which comprises sinoatrial node (SA node), atrioventricular node (AV node) and various kinds of nerve fibers. The pacemaking system is very precise so as to maintain the most essential rhythm of life. Nevertheless, to cope with various environments inside and outside human bodies, human bodies are equipped with the autonomic nervous system including the sympathetic nervous system and the parasympathetic nervous system for regulation of heart rate. The former increases the heart rate, whereas the latter decreases it. Owing to the interaction of the two nervous systems, heart rate is kept in an optimal state of equilibrium. In addition to their different effects, the two nervous systems function at different speeds. The sympathetic nerves work slowly, and the parasympathetic nerves (especially the vagus nerve, which controls heart rate) function fast. Mankind has known the discrepancy between the respective speeds of these two different kinds of nervous systems for a long time. However, in the past, the analytical instruments were not sophisticated enough to enable the evaluation of this characteristic or persuade people that it is worth using.
Moreover, as discovered by researchers, although a normal adult's heart maintains at around 70 beats per minute during a static state, there are some regular or irregular fluctuations in the hear rate. Fast or slow, regular or random, the fluctuations were usually ignored in medical researches conducted in the past because of their minute amplitudes. Nonetheless, according to some experts, part of the fluctuations keeps pace with breathing, though the remainder has nothing to do with breath. In this regard, little can be achieved with conventional analytical methods for two reasons. First, the amplitudes of the fluctuations are too small to be observed by means of any conventional recorder, and thus researchers have to adopt invasive experimental methods in order to excite the fluctuations to such an extent that it is feasible to measure them. Secondly, there was not any method suitable for the quantitative, statistical analysis of the fluctuations despite their occurrence.
In recent years, plenty of new technologies to evaluate the autonomic functions were successfully developed. Given the sophisticated computer hardware and software know-how available, today it is possible to detect and perform quantitative analysis of a person autonomic cardiac activity in light of the minute fluctuations of hear rate, known as heart rate variability (HRV), taken while the person is at rest. In other words, the new technologies allow a user to analyze or evaluate a normal person's autonomic functions without interfering with the person's daily life. Heart rate variability analysis stands out above other methods for evaluation of autonomic functions, because it has the following advantages: (1) being a non-invasive diagnosis technology, it does not cause a subject any pain, (2) the hardware it uses is cheap, thus it has the potential for large-scale promotion, and (3) many animal tests and human tests prove that it evaluates autonomic functions accurately. Therefore, the technology of heart rate variability analysis is in wide use in recent years, and related research is conducted on it unceasingly.
The advent of the technology about spectrum analyzers in the early 1980s enabled heart rate variability analysis to be brought into full play, when autonomic functions were quantitatively analyzed in light of the beating cycle of heart. Hence, heart rate variability analysis gradually becomes the best non-invasive method for detecting autonomic functions.
With spectrum analysis, researchers discovered that the minute fluctuations of heart rate variability can be definitely divided into two groups, that is, high-frequency (HF) component and low frequency (LF) component. The HF component is synchronous to animals breath signals, so it is also known as breath component, which occurs approximately every three seconds in a human being. The source of the LF component that takes place approximately every ten seconds in a human being remains unidentified, though researchers infer that they are relevant to vascular motion or baroreflex. Some academics went further to divide the LF component into two categories, that is, very low frequency (VHF) component and low frequency component. At present, many physiologists and cardiologists believe that the HF component or total power (TP) reflects parasympathetic functions, whereas the ratio of LF component to HF component (LF/HF) reflects sympathetic activity. In addition to being an index of autonomic functions, heart rate variability reflects various kinds of information about human bodies, as indicated by some researches. For instance, patients diagnosed with intracranial hypertension usually have relatively low heart rate variability, the death rate of an elder whose LF component of heart rate variability decreases by a standard deviation is 1.7 times that of normal persons, and the LF component of heart rate variability vanishes in a brain-dead person. Furthermore, there are changes in heart rate variability in a patient who exhibits rejection reactions after heart transplantation. During an operation, heart rate variability reflects depth of anesthesia. Gender and age certainly determine sympathetic functions and parasympathetic functions. For example, sympathetic functions and parasympathetic functions are active in young persons, but rather inactive in old persons; in males, sympathetic functions prevail but parasympathetic functions yield; conversely, parasympathetic functions excel sympathetic functions in females. Afterward, the fact that women's sympathetic functions increase during pregnancy, is found in hospitals, but any overreaction may be complicated by, or even contribute to, life-threatening preeclampsia.
In 1996, European and American cardiology societies standardized and published the analytical method of heart rate variability (Circulation (1996), 17, pp. 354-381), which is shown in the flowchart of FIG. 1. In the first place, capturing an electrocardiogram signal, and then digital sampling and noise filtering are performed by a microprocessor. Sequentially, the RR data (RR peak-to-peak intervals) of the captured electrocardiogram signal is edited, and any unsatisfactory RR peak-to-peak intervals is removed to acquire the RR peak-to-peak intervals generated by normal rhythmic points, which is called NN data. The heart rate variability is acquired by conducting spectrum analysis of frequency domain followed by performing interpolation and sampling to the NN data. However, this method is rather complicated and trivial, and researchers have to identify noise, edit RR data and eliminate them manually, and thus it requires considerable manpower and time to accomplish the chores. Hence, the aforesaid method constitutes a high threshold for laymen to gain access to the method.
At present, heart rate variability is mostly analyzed by a digital computer. An electrocardiogram signal is captured and analog-to-digital conversion is performed on it, and then the converted electrocardiogram signal is stored in a digital file. Meanwhile, it is necessary to provide an identification code or a filename for the digital file. Any correction or analysis carried out to the digital file has to be done manually. Upon completion of the analysis, data also has to be printed out manually.
In short, with a conventional method, the process of analysis of heart rate variability, from signal retrieval to file analysis and eventually printout processing, has to be performed manually. In this regard, a keyboard is the usual medium of operation. As a result, the analytical process of heart rate variability involves a lot of keystrokes performed on the part of a researcher and, worse yet, it also involves pressing different types of keys on the keyboard. In addition, equipped with a keyboard, a machine designed to analyze heart rate variability design can never be smaller; this does not conform to the current trend of miniaturization of machines.